Background : Seasonal variations in the incidence of Coronary Heart Disease (CHD) have rarely been studied qualitatively and quantitatively, although it is often pointed out that CHD is more likely to happen in winter. Methods and Results : We analyzed the 10 year population-based data by using Logistic Regression and Poisson Regression Models to examine seasonal variations and the effect of atmospheric temperature on the incidence of CHD in Hiroshima City, Japan. There were 3755 incident events, 63.33% days on which CHD events occurred and 1.03 events per day. Relative Risk (RR) for winter, spring and autumn in comparison with summer was 1.53, 1.25 and 1.24 respectively, and there were 30.0%, 19.4% and 19.2% more events than in summer. In contrast with September, there was a higher risk in January (RR=1.99, p<0.001), November (RR=1.65, p=0.003) and December (RR=1.58, p=0.006), whereas the risk in June (RR=1.06, p>0.05) and July (RR=1.00, p>0.05) was as low as September. Atmospheric temperature had a statistically significant effect on CHD incidence. Odds ratios and risk ratios estimated by Logistic Regression Model and Poisson Regression Model were all higher when the daily mean atmospheric temperature was lower than 18℃, the highest risk occurring below 4℃. Lower risks were observed from 18 to 30℃ and the lowest risk was found at 28-30℃. Conclusions : The incidence of CHD shows a more than 50% higher value in winter than in summer. There exists a higher risk on cold days, especially when the daily mean temperature is below 4℃.